32 citations · 53 across the 9 of their papers we have counts for
10 papers
I Can't Believe It's Not Better: In-air Movement For Alzheimer Handwriting Synthetic Generation
Asma Bensalah, Antonio Parziale, Giuseppe De Gregorio +3
During recent years, there here has been a boom in terms of deep learning use for handwriting analysis and recognition. One main application for handwriting analysis is early detec…
The RPM3D project: 3D Kinematics for Remote Patient Monitoring
Alicia Fornés, Asma Bensalah, Cristina Carmona-Duarte +9
This project explores the feasibility of remote patient monitoring based on the analysis of 3D movements captured with smartwatches. We base our analysis on the Kinematic Theory of…
A Few Shot Multi-Representation Approach for N-gram Spotting in Historical Manuscripts
Giuseppe De Gregorio, Sanket Biswas, Mohamed Ali Souibgui +4
Despite recent advances in automatic text recognition, the performance remains moderate when it comes to historical manuscripts. This is mainly because of the scarcity of available…
Doc2Graph: a Task Agnostic Document Understanding Framework based on Graph Neural Networks
Andrea Gemelli, Sanket Biswas, Enrico Civitelli +2
Geometric Deep Learning has recently attracted significant interest in a wide range of machine learning fields, including document analysis. The application of Graph Neural Network…
A Generic Image Retrieval Method for Date Estimation of Historical Document Collections
Adrià Molina, Lluis Gomez, Oriol Ramos Terrades +1
Date estimation of historical document images is a challenging problem, with several contributions in the literature that lack of the ability to generalize from one dataset to othe…
Text-DIAE: A Self-Supervised Degradation Invariant Autoencoders for Text Recognition and Document Enhancement
Mohamed Ali Souibgui, Sanket Biswas, Andres Mafla +6
In this paper, we propose a Text-Degradation Invariant Auto Encoder (Text-DIAE), a self-supervised model designed to tackle two tasks, text recognition (handwritten or scene-text)…
DocEnTr: An End-to-End Document Image Enhancement Transformer
Mohamed Ali Souibgui, Sanket Biswas, Sana Khamekhem Jemni +4
Document images can be affected by many degradation scenarios, which cause recognition and processing difficulties. In this age of digitization, it is important to denoise them for…
DocSegTr: An Instance-Level End-to-End Document Image Segmentation Transformer
Sanket Biswas, Ayan Banerjee, Josep Lladós +1
Understanding documents with rich layouts is an essential step towards information extraction. Business intelligence processes often require the extraction of useful semantic conte…
Graph-based Deep Generative Modelling for Document Layout Generation
Sanket Biswas, Pau Riba, Josep Lladós +1
One of the major prerequisites for any deep learning approach is the availability of large-scale training data. When dealing with scanned document images in real world scenarios, t…
DocSynth: A Layout Guided Approach for Controllable Document Image Synthesis
Sanket Biswas, Pau Riba, Josep Lladós +1
Despite significant progress on current state-of-the-art image generation models, synthesis of document images containing multiple and complex object layouts is a challenging task.…